---
title: "Statistics"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
# rm(list=ls())

library(flexdashboard)
library(ggplot2)
library(plotly)
library(tidyr)
library(readxl)
library(leaflet)
library(stringr)
library(DT)

cob_sub_merge <- read.csv("Country of birth of people aged 15-24 by Suburb.csv",stringsAsFactors = F)

#VPHS data
psy_dist <- read.csv("Level of psychological distress 2015-19.csv",stringsAsFactors = F)

diag_anxdep <- read.csv("Ever diagnosed with anxiety or depression 2015-19.csv",stringsAsFactors = F)

```

Column {.tabset .tabset-fade}
-----------------------------------------------------------------------

### **Level of Psychological distress**

```{r Level of Psychological distress, echo=FALSE}
# Level of Psychological distress

psy_dist_graph <- psy_dist %>%
  gather(key,value,-Year) %>%
  mutate(value=as.integer(value))

psy_dist_graph$key <- factor(psy_dist_graph$key,levels=c('Low','Moderate','High','Very_High', 'High_or_Very_High'))
sizes <- c('Low' = 1, 'Moderate' = 1, 'High' = 1, 'Very_High' = 1, 'High_or_Very_High' = 1)


lpd <- ggplot(psy_dist_graph,aes(x=Year,y=value,group=key,color=key))+
  geom_point()+
  labs(title =str_wrap('Changes in the level of psychological distress for Victorian adults over the years'),
    subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), by level of psychological distress changes in Victoria over 2015-2019. The higher level of psychological distress for was the highest in 2019."),
       caption = "•Data obtained from Victorian Population Health Survey",
       x='',
       y='Number of people') +
  geom_line(aes(colour = key, size = key, group = key)) +
  scale_size_manual(values = sizes) +
  scale_color_manual(values = c(rcartocolor::carto_pal(name = "Bold"), "grey50"))+ 
  theme_bw()
lpd
```

### **Diagnosed with anxiety/depression**

```{r Diagnosed with anxiety/depression, echo=FALSE}

names(diag_anxdep) <- c("Year","Proportion_of_people")

diag_ad_graph <-ggplot(diag_anxdep,aes(x=Year,y=Proportion_of_people))+
    geom_line(size=1,color="#0174DF")+
  geom_point(size=4,shape=21,fill="white") +
  labs(title =str_wrap('Proportion of adults that were diagnosed with anxiety or depression over time'),
    subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), with anxiety or depression in Victoria over 2015-2019. The proportion of adults has been gradually increasing over the years."),
       caption = "•Data obtained from Victorian Population Health Survey",
    x="",
    y="Proportion of people")+
  theme_bw()

diag_ad_graph
```

---
    title: "Statistics"
    output: 
      flexdashboard::flex_dashboard:
        orientation: columns
        social: menu
        source_code: embed
    ---
    
    ```{r setup, include=FALSE}
    # rm(list=ls())
    
    library(flexdashboard)
    library(ggplot2)
    library(plotly)
    library(tidyr)
    library(readxl)
    library(leaflet)
    library(stringr)
    library(DT)
    
    cob_sub_merge <- read.csv("Country of birth of people aged 15-24 by Suburb.csv",stringsAsFactors = F)
    
    #VPHS data
    psy_dist <- read.csv("Level of psychological distress 2015-19.csv",stringsAsFactors = F)
    
    diag_anxdep <- read.csv("Ever diagnosed with anxiety or depression 2015-19.csv",stringsAsFactors = F)
    
    ```
    
    Column {.tabset .tabset-fade}
    -----------------------------------------------------------------------
    
    ### **Level of Psychological distress**
    
    ```{r Level of Psychological distress, echo=FALSE}
    # Level of Psychological distress
    
    psy_dist_graph <- psy_dist %>%
      gather(key,value,-Year) %>%
      mutate(value=as.integer(value))
    
    psy_dist_graph$key <- factor(psy_dist_graph$key,levels=c('Low','Moderate','High','Very_High', 'High_or_Very_High'))
    sizes <- c('Low' = 1, 'Moderate' = 1, 'High' = 1, 'Very_High' = 1, 'High_or_Very_High' = 1)
    
    
    lpd <- ggplot(psy_dist_graph,aes(x=Year,y=value,group=key,color=key))+
      geom_point()+
      labs(title =str_wrap('Changes in the level of psychological distress for Victorian adults over the years'),
        subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), by level of psychological distress changes in Victoria over 2015-2019. The higher level of psychological distress for was the highest in 2019."),
           caption = "•Data obtained from Victorian Population Health Survey",
           x='',
           y='Number of people') +
      geom_line(aes(colour = key, size = key, group = key)) +
      scale_size_manual(values = sizes) +
      scale_color_manual(values = c(rcartocolor::carto_pal(name = "Bold"), "grey50"))+ 
      theme_bw()
    lpd
    ```
    
    ### **Diagnosed with anxiety/depression**
    
    ```{r Diagnosed with anxiety/depression, echo=FALSE}
    
    names(diag_anxdep) <- c("Year","Proportion_of_people")
    
    diag_ad_graph <-ggplot(diag_anxdep,aes(x=Year,y=Proportion_of_people))+
        geom_line(size=1,color="#0174DF")+
      geom_point(size=4,shape=21,fill="white") +
      labs(title =str_wrap('Proportion of adults that were diagnosed with anxiety or depression over time'),
        subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), with anxiety or depression in Victoria over 2015-2019. The proportion of adults has been gradually increasing over the years."),
           caption = "•Data obtained from Victorian Population Health Survey",
        x="",
        y="Proportion of people")+
      theme_bw()
    
    diag_ad_graph
    ```